Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and applied research within communication, networks, control
-
to evolve classical communication networks to support both traditional data and the unique requirements of quantum information systems (https://www.classique.aau.dk). CLASSIQUE will address a suite of
-
the analysis of organizing processes and their outcomes. Methodologically, we value qualitative research methods highly and often adopt case study, field work methodology or social network analysis. The teaching
-
of greenhouse gases including CO2 and CH4. The PhD project is part of the Horizon Europe Marie Sklodowska-Curie Action (MSCA) doctoral network (DN) ELEGANCE (machinE LEarning for inteGrated multi-parAmetric
-
carbon electrodes developed in the network. You will leverage advanced data analysis methods such as Distribution of Diffusion Times to obtain insight into mass transfer and microstructural effects in
-
Job Description Do you want to be part of the circular revolution to rethink the way we value the built environment? Join us as a fully-funded PhD in the MSCA doctoral network QuiVal - Quantum
-
Design invites applications for a PhD stipend in the field of causal discovery and spatiotemporal analysis of brain signals. The stipend is within the general study programme Electrical and Electronic
-
(BRIGHT). These PhD positions are part of the BUG-ID Marie Skłodowska-Curie Doctoral Training Network (DN), funded by the European Commission. BUG-ID consortium has a mission to improve infection
-
@biosustain.dtu.dk MSCA doctoral network ELEGANCE website: https://elegance.dtu.dk/ Google Scholar profile: https://scholar.google.com/citations?hl=en&user=yZDS88IAAAAJ More information about DTU Biosustain
-
of the BUG-ID Marie Skłodowska-Curie Doctoral Training Network (DN), funded by the European Commission. BUG-ID consortium has a mission to improve infection diagnostics. All BUG-ID PhD students will be